Back to Catalog

Improve Customer Support with AI-powered Voice Services

IntermediateGuided Project

In this guided project, you will create a voice-enabled pizza-ordering application using embeddable AI and deploy it with Flask. Learn how to use Flask to deploy machine-learning models, allowing anyone to interact with them through an intuitive user interface and see the results for themselves. Don't let the challenge of training AI hold you back - our cutting-edge embeddable AI libraries can be seamlessly integrated into your enterprise applications.

4.5 (346 Reviews)

Language

  • English

Topic

  • Artificial Intelligence

Industries

  • Retail, Software Developer, Marketing, Information Technology

Enrollment Count

  • 1.83K

Skills You Will Learn

  • Artificial Intelligence, Natural Language Processing, Web Development, Embeddable AI, AI

Offered By

  • IBM

Estimated Effort

  • 50 minutes

Platform

  • SkillsNetwork

Last Update

  • May 9, 2025
About this Guided Project
Image resource: PxHere 
Do you want to unlock the full potential of your workforce with AI - Cut costs, maximize human talent, and tackle higher-value tasks with ease using IBM Research's latest embeddable AI solutions? These days, many organizations are implementing AI to minimize the costs of repetitive and routine tasks that can be performed by technology while maximizing the talent of their human resources. By removing such repeating tasks from human workers' responsibilities, AI frees workers to move to higher-value and complex tasks that technology can't handle.

Yet, training AI can be a bit of a challenge for most companies. It takes time, knowledge, and expertise to do it properly, but don't let that stop you. IBM Research has got you covered. They've recently added three new software libraries to their collection of embeddable AI solutions. These tools can be smoothly integrated into enterprise applications, making it easy to tackle a variety of tasks.

In this guided project, we will take a straightforward approach to show you the magic of embeddable AI. More importantly, we will teach you how to use Flask to deploy machine-learning models, so anyone can interact with them through an excellent user interface and know what you have accomplished. Perfect for developers with experience in Python and HTML, but struggling to implement ML models in their applications. Bridge the gap and take your business to the next level with this easy-to-follow project!


A Look at the Project Ahead

After completing this guided project you will be able of:
  • Transform your application with cutting-edge machine learning models.
  • Master the essentials of Flask and elevate your frontend development skills.
  • Revolutionize the way you order online by building your own voice ordering web app with Flask.

What You'll Need

This project primarily employs Python and HTML to construct the web app. However, prior knowledge of ML is not necessary to get started and we welcome all participants, regardless of experience, to take part in this guided project.

Frequently Asked Questions

  • Do I need to install any software to participate in this project?
    Everything you need to complete this project will be provided to you via the Cloud IDE and it will all be available via a standard web browser.


  • What web browser should I use?
    The Cloud IDE platform works best with current versions of Chrome Chrome(v47+), Edge, Firefox (v25+), or Safari.

Instructors

Sheng-Kai Chen

Data Scientist

Sheng-Kai Chen is a graduate student at the University of Toronto, concentrating on Information Systems & Design. Having several experiences analyzing data for retail stores and designing small software for small businesses. Sheng-Kai was inspired to shift toward answering new challenges with machine learning and new technics.

Read more

Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

Read more

Contributors

Roxanne Li

Data Scientist at IBM

I am an aspiring Data Scientist at IBM with extensive theoretical/academic, research, and work experience in different areas of Machine Learning, including Classification, Clustering, Computer Vision, NLP, and Generative AI. I've exploited Machine Learning to build data products for the P&C insurance industry in the past. I also recently became an instructor of the Unsupervised Machine Learning course by IBM on Coursera!

Read more

J.C.(Junxing) Chen

Data scientist at IBM

Data science is easy and helpful! I want to let everyone know data science and help everyone using it for everyday life! Not only being a Data science guide person but also making friends, I want to make friends with peoples like you! As a data scienist, I hope my spread data science could help my friend!

Read more

Artem Arutyunov

Data Scientist

Hey, Artem here! I am excited about answering new challenges with data science, machine learning and especially Reinforcement Learning. Love helping people to learn, and learn myself. Studying Math and Stats at University of Toronto, hit me up if you are from there as well.

Read more

Sina Nazeri

Data Scientist at IBM

I am grateful to have had the opportunity to work as a Research Associate, Ph.D., and IBM Data Scientist. Through my work, I have gained experience in unraveling complex data structures to extract insights and provide valuable guidance.

Read more